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Record W2320264398 · doi:10.1021/jf402473u

Flavor of Cold-Hardy Grapes: Impact of Berry Maturity and Environmental Conditions

2013· article· en· W2320264398 on OpenAlexaffabout
Karine Pedneault, Martine Dorais, Paul Angers

Bibliographic record

VenueJournal of Agricultural and Food Chemistry · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFermentation and Sensory Analysis
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsBerryFlavorMaturity (psychological)Food scienceChemistryHorticultureBiologyPsychology

Abstract

fetched live from OpenAlex

Since the arrival on the market of high-quality cold-hardy grape varieties, northern winemaking has been developing tremendously in countries traditionally unsuited for grape and wine production. Cold-hardy grapes are mainly interspecific hybrids of Vitis vinifera with Vitis labrusca and Vitis riparia , making their chemical composition distinct from that of V. vinifera varieties traditionally used for winemaking and therefore limiting the use of current knowledge about V. vinifera varieties in the assessment of grape maturity. Consequently, to evaluate the flavor development of cold-hardy grapes in the province of Quebec, Canada, the ripening of Frontenac and Marquette berries in two vineyards located in the southwest (SW) and northeast (NE) areas of the province, starting at the beginning of veraison, was studied. Quality attributes, phenolic compounds, and aroma profiles showed significant changes during maturation. Although full maturity was reached for both Frontenac and Marquette in the SW vineyard (1380 accumulated growing degree days, based on 10 °C), the accumulation of 1035 growing degree days was not sufficient to fully ripen Frontenac and Marquette in the NE vineyard. Principal component analysis showed different ripening patterns for the two studied locations. The longer veraison in the SW vineyard resulted in higher quality attributes and higher flavor development for both Frontenac and Marquette. Under the colder conditions in the NE vineyard, metabolite accumulation was driven primarily by berry growth, and flavor development was limited. Besides growing degree days and technological parameters (total soluble solids, pH, titratable acidity), which provide significant guidelines for maturity assessment in cold climate, phenolic maturity may be followed by the accumulation of hydroxycinnamic esters and flavonoids, although the impact of these compound classes on quality remains to be determined in cold-climate wines. In both Frontenac and Marquette, aromatic maturity was best assessed using the ratio of cis-3-hexenol to trans-2-hexenal, which showed a constant decrease until maturity. Interestingly, a shift in C6 compound profile, illustrated by the progression of the sum of C6 compounds respectively produced from linoleic (C18:2; hexanal and 1-hexanol) and α-linolenic (C18:3; trans-2-hexenol and cis-3-hexenol) acids occurred during ripening, with α-linolenic acid (C18:3) degradation products decreasing in both varieties as maturation approached. At harvest, aroma profiles of both Frontenac and Marquette were dominated by C6 compounds (hexanal, trans-2-hexenal, 1-hexanol, cis-3-hexenol, and hexanoic acid), acetic acid, β-damascenone, and 2-phenylethanol, with Marquette additionally showing significant levels of monoterpenes (linalool, geraniol, and α-citral) and 1-octen-3-ol.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.082
Threshold uncertainty score0.163

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.196
Teacher spread0.188 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations67
Published2013
Admission routes2
Has abstractyes

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